Empirical Research On Price Discovery Function And Quantitative Trading Strategy Of Rebar Futures

Since rebar futures has been listed on the Shanghai futures exchange on March27,2009, the market is much favored by investors. However, relative to the domestic futures varieties, such as agricultural futures and copper futures, time to market of rebar futures is much shorter, it’s still in the early stages of development. Therefore, whether the function of the futures market can be played effective are the key problem.The futures market has two basic functions:the hedging function and price discovery function. The function of price discovery is not only the basis for the existence and development of the futures market but also the basic premise of spot market guiding the futures market. The operation efficiency of futures market can be measured by this function. At the same time, in our country, the listed on of metal futures after the commodity of rapeseed oilpalm oil futures, strengthens the interaction between the futures market and stock market, also with the spot market. Investors can either make hedging between futures market, stock market and spot market or make risky speculation in the futures market. The strong rapid development of futures market and the expansion of financial derivative market provide basic market for quantitative trading. Using quantitative trading in futures market will be an important direction of development to market investors, especially institutional investors.This thesis is divided into two parts. Part one, the efficiency of price discovery function of rebar futures to futures market is studied. Key factors that influence the price discovery of futures can be revealed in the empirical study of relationship which is about future price and spot price. Part two, establish quantitative trading model of rebar futures with its five minute date, then MATLAB simulation language is been used to analyze thus model in order to work out the optimal quantitative trading strategies.Methods adopted in the empirical research which is about Rebar future market price discovery function are ADF unit root test, co-integration test,vector autoregression model, vector error correction model, EG two step test, Granger causality test and variance decomposition. The tool used here is EVIEWS. The data selected is daily closing price of rebar future. Sample interval is from September1,2009to March10,2014which has removed the first five months after the listed on of rebar futures. The empirical results show that:(1)the rebar futures prices and spot prices are non-stationary series with stable first differences;(2) there is a co-integration relationship between rebar futures prices and spot prices of rebar, that is long-term equilibrium relationship;(3)there is a bi-directional leading relationship between rebar price in future and spot market, but compared with spot market, futures market has advantage on information absorbing;(4) futures prices is in the dominant position, but the market still need to continue to improve as its intensity that it played is not strong enough.Short-term trading mode is been used to make Quantitative trade strategy. Short term trading doesn’t give a clear time limit; it can be several days, couple of hours or even a minute. The definition of short-term in this thesis is limited to be5minutes. Sample interval is from January27,2014to March11,2014. K-line technology method and technology index method are used as the empirical research methods. Technology index method contains technical indicators with trend such as MACD and MA as well as technical indexes with turmoil such as KDJ and RSI. Trading strategy is divided into two steps. The first step (so-called double index portfolio strategy) is to find the optimal parameter set through the combination of every index them. Such as the moving average line(MA) can be five days moving average, ten days moving average, fifteen days moving average and so on. The optimum parameters is to be determined by profit rate, win ratio and so on through the combinations constituted by different day of moving average,. The second step (so-called four index portfolio strategy) is to let the default parameters of each index to be equal to optimal parameters obtained in the first step, then analyze the resonance and superimposed on the modified index. Trading strategies results show that:funds utilization rate and capital return rate of index portfolio ratio are higher than the single index used alone. At the same time, the four index portfolio strategy performance to maintain a high rate of return, improve the win ratio and reduce the maximum profit rate and the maximum loss rate as well as remain the profit-risk ratio at a high level.